Downloads · 30 days
4
20% of all-time downloads
job-2ffde234-0b7c-4390-bcb7-bdaf5ec148fc
Shree1007/job-2ffde234-0b7c-4390-bcb7-bdaf5ec148fc
job-2ffde234-0b7c-4390-bcb7-bdaf5ec148fc is a machine learning model from Shree1007. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This model is a custom, decoder-only Transformer trained from scratch using a private pipeline.
All-time downloads
20
Public
Repo size
354 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin354 MB · 100%
At a glance
- License
- mit
- Model type
- gpt2
- Access
- Public
- Created
- Sep 28, 2025
- Updated
- Sep 28, 2025
- SHA
- fd37a2ae
Model card
From the Hugging Face model README
Custom Transformer Model: job-2ffde234-0b7c-4390-bcb7-bdaf5ec148fc
This model is a custom, decoder-only Transformer trained from scratch using a private pipeline.
- Job ID: job-2ffde234-0b7c-4390-bcb7-bdaf5ec148fc
- Model Description: A story telling transformer
- Parameters: 88,500,307
- Architecture:
- Layers: 12
- Attention Heads: 12
- Embedding Dimension: 768
How to Use
This model requires trusting remote code to load the custom Transformer class. The model architecture code would need to be provided alongside the model weights for loading, typically in modeling_transformer.py.
from transformers import AutoTokenizer, AutoModelForCausalLM
repo_id = "YourHFUsername/job-2ffde234-0b7c-4390-bcb7-bdaf5ec148fc" # Replace with your HF username and the job ID
# Load the tokenizer
tokenizer = AutoTokenizer.from_pretrained(repo_id)
# Load the model
# trust_remote_code=True is essential to load the custom architecture
model = AutoModelForCausalLM.from_pretrained(repo_id, trust_remote_code=True)
- Type
- gpt2
- License
- mit
- Languages
- en
- Created
- Sep 28, 2025
- Updated
- Sep 28, 2025